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distilbert-base-uncased-lora-text-classification
erwinyonata/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from erwinyonata. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 14, 2024
- Updated
- May 14, 2024
- SHA
- 369f99ab
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7392
- Accuracy: {'accuracy': 0.901}
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.2589 | {'accuracy': 0.896} |
| No log | 2.0 | 250 | 0.4331 | {'accuracy': 0.868} |
| No log | 3.0 | 375 | 0.3884 | {'accuracy': 0.901} |
| 0.2587 | 4.0 | 500 | 0.4673 | {'accuracy': 0.895} |
| 0.2587 | 5.0 | 625 | 0.6184 | {'accuracy': 0.899} |
| 0.2587 | 6.0 | 750 | 0.6478 | {'accuracy': 0.902} |
| 0.2587 | 7.0 | 875 | 0.7249 | {'accuracy': 0.899} |
| 0.0338 | 8.0 | 1000 | 0.7446 | {'accuracy': 0.893} |
| 0.0338 | 9.0 | 1125 | 0.7290 | {'accuracy': 0.9} |
| 0.0338 | 10.0 | 1250 | 0.7392 | {'accuracy': 0.901} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- May 14, 2024
- Updated
- May 14, 2024